Using calculated values for scoring in conversations
There are many uses for calculated values in conversations. A good use case is scoring the results of a conversation. In the example below, patients are completing the mRS survey (Modified Rankin Scale) which is used for patients post-stroke to categorize level of functional independence. Based on how the patient responds, they will be assigned a score.
In the conversation builder, create clear coding of responses. In this example, coding is as follows:
QuestionID | Question |
|---|---|
live_alone | Could you live alone without any help from another person? This means being able to bathe, use the toilet, shop, prepare or get meals, and manage finances. |
able_before_stroke | Are you able to do everything that you were doing right before your stroke, even if slower and not as much? |
walk_alone | Are you able to walk without help from another person? |
completely_back | Are you completely back to the way you were right before your stroke? |
bedridden | Are you bedridden or needing constant supervision? |
Next, go to survey settings > logic > create the calculated values below. Make sure to check the “include into result” checkbox next to the calculated value so the values will be available in W2H for evaluation. Click “OK” to save.
Here is a snippet of the nested iif statements shown in the screenshot above:
iif( {able_before_stroke} = "N", 2,
iif( {walk_alone} = "Y", 3,
iif( {completely_back} = "Y", 0,
iif( {completely_back} = "N", 1,
iif( {bedridden} = "N", 4,
iif( {bedridden} = "Y", 5, 'null')))){mrs_score} functions like an [if, else if, else if, else] categorization mechanism from top to bottom. This means that if one criteria is met, then the evaluation will stop, otherwise it will proceed to the next row. If none of the criteria are met, the {mrs_score} will be null. This is the case if the conversation is not completed.